{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using backend: pytorch\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from cFPCT_DNN import cFPCT_DNN\n",
    "from TestCases import HighFrequencyCase1, HighFrequencyCase2, HighFrequencyCase3, AKG, Helmholtz, HighFrequencyCase2D1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling model...\n",
      "'compile' took 0.000127 s\n",
      "\n",
      "Training model...\n",
      "\n",
      "Step      Train loss              Test loss               Test metric\n",
      "0         [2.11e+06, 1.26e+00]    [2.11e+06, 1.26e+00]    []  \n",
      "1000      [1.23e+02, 3.91e-01]    [1.20e+02, 3.91e-01]    []  \n",
      "2000      [2.14e+01, 3.94e-01]    [2.10e+01, 3.94e-01]    []  \n",
      "3000      [2.21e+00, 3.96e-01]    [2.16e+00, 3.96e-01]    []  \n",
      "4000      [1.16e+00, 3.97e-01]    [1.13e+00, 3.97e-01]    []  \n",
      "5000      [7.71e-01, 3.96e-01]    [7.51e-01, 3.96e-01]    []  \n",
      "6000      [4.07e-01, 3.96e-01]    [3.96e-01, 3.96e-01]    []  \n",
      "7000      [4.16e-01, 3.96e-01]    [4.06e-01, 3.96e-01]    []  \n",
      "8000      [9.81e-02, 3.96e-01]    [9.52e-02, 3.96e-01]    []  \n",
      "9000      [5.87e-02, 3.96e-01]    [5.69e-02, 3.96e-01]    []  \n",
      "10000     [4.60e-02, 3.96e-01]    [4.46e-02, 3.96e-01]    []  \n",
      "11000     [5.74e-02, 3.96e-01]    [5.63e-02, 3.96e-01]    []  \n",
      "12000     [8.89e+00, 3.96e-01]    [8.89e+00, 3.96e-01]    []  \n",
      "13000     [4.11e-02, 3.96e-01]    [3.99e-02, 3.96e-01]    []  \n",
      "14000     [4.06e-02, 3.96e-01]    [3.94e-02, 3.96e-01]    []  \n",
      "15000     [5.38e-02, 3.96e-01]    [5.25e-02, 3.96e-01]    []  \n",
      "16000     [4.12e-02, 3.96e-01]    [4.00e-02, 3.96e-01]    []  \n",
      "17000     [3.86e-02, 3.96e-01]    [3.75e-02, 3.96e-01]    []  \n",
      "18000     [2.57e-01, 3.96e-01]    [2.55e-01, 3.96e-01]    []  \n",
      "19000     [4.27e+00, 3.96e-01]    [4.28e+00, 3.96e-01]    []  \n",
      "20000     [7.81e+01, 3.94e-01]    [7.82e+01, 3.94e-01]    []  \n",
      "21000     [3.62e-02, 3.96e-01]    [3.52e-02, 3.96e-01]    []  \n",
      "22000     [4.23e-01, 3.96e-01]    [4.23e-01, 3.96e-01]    []  \n",
      "23000     [4.47e+00, 3.95e-01]    [4.47e+00, 3.95e-01]    []  \n",
      "24000     [4.05e-01, 3.96e-01]    [4.05e-01, 3.96e-01]    []  \n",
      "25000     [1.83e+01, 3.97e-01]    [1.83e+01, 3.97e-01]    []  \n",
      "26000     [3.51e-02, 3.96e-01]    [3.41e-02, 3.96e-01]    []  \n",
      "27000     [3.42e-02, 3.96e-01]    [3.33e-02, 3.96e-01]    []  \n",
      "28000     [3.17e-02, 3.96e-01]    [3.07e-02, 3.96e-01]    []  \n",
      "29000     [1.03e-01, 3.96e-01]    [1.02e-01, 3.96e-01]    []  \n",
      "30000     [3.05e-02, 3.96e-01]    [2.96e-02, 3.96e-01]    []  \n",
      "31000     [3.07e-02, 3.96e-01]    [2.98e-02, 3.96e-01]    []  \n",
      "32000     [2.94e-02, 3.96e-01]    [2.86e-02, 3.96e-01]    []  \n",
      "33000     [2.90e-02, 3.96e-01]    [2.82e-02, 3.96e-01]    []  \n",
      "34000     [1.40e-01, 3.96e-01]    [1.40e-01, 3.96e-01]    []  \n",
      "35000     [2.82e-02, 3.96e-01]    [2.73e-02, 3.96e-01]    []  \n",
      "36000     [2.77e-02, 3.96e-01]    [2.69e-02, 3.96e-01]    []  \n",
      "37000     [2.72e-02, 3.96e-01]    [2.64e-02, 3.96e-01]    []  \n",
      "38000     [3.95e-02, 3.96e-01]    [3.89e-02, 3.96e-01]    []  \n",
      "39000     [2.62e-02, 3.96e-01]    [2.54e-02, 3.96e-01]    []  \n",
      "40000     [2.60e-02, 3.96e-01]    [2.52e-02, 3.96e-01]    []  \n",
      "41000     [2.55e-02, 3.96e-01]    [2.48e-02, 3.96e-01]    []  \n",
      "42000     [2.50e-02, 3.96e-01]    [2.42e-02, 3.96e-01]    []  \n",
      "43000     [4.48e+01, 3.95e-01]    [4.48e+01, 3.95e-01]    []  \n",
      "44000     [2.43e-02, 3.96e-01]    [2.35e-02, 3.96e-01]    []  \n",
      "45000     [2.02e-01, 3.96e-01]    [2.02e-01, 3.96e-01]    []  \n",
      "46000     [2.37e-02, 3.96e-01]    [2.30e-02, 3.96e-01]    []  \n",
      "47000     [2.33e-02, 3.96e-01]    [2.26e-02, 3.96e-01]    []  \n",
      "48000     [2.30e-02, 3.96e-01]    [2.23e-02, 3.96e-01]    []  \n",
      "49000     [2.26e-02, 3.96e-01]    [2.19e-02, 3.96e-01]    []  \n",
      "50000     [2.23e-02, 3.96e-01]    [2.16e-02, 3.96e-01]    []  \n",
      "51000     [2.19e-02, 3.96e-01]    [2.13e-02, 3.96e-01]    []  \n",
      "52000     [2.15e-02, 3.96e-01]    [2.09e-02, 3.96e-01]    []  \n",
      "53000     [2.11e-02, 3.96e-01]    [2.05e-02, 3.96e-01]    []  \n",
      "54000     [2.11e-02, 3.96e-01]    [2.04e-02, 3.96e-01]    []  \n",
      "55000     [2.07e-02, 3.96e-01]    [2.01e-02, 3.96e-01]    []  \n",
      "56000     [2.03e-02, 3.96e-01]    [1.97e-02, 3.96e-01]    []  \n",
      "57000     [2.00e-02, 3.96e-01]    [1.94e-02, 3.96e-01]    []  \n",
      "58000     [1.95e-02, 3.96e-01]    [1.89e-02, 3.96e-01]    []  \n",
      "59000     [1.94e-02, 3.96e-01]    [1.89e-02, 3.96e-01]    []  \n",
      "60000     [1.91e-02, 3.96e-01]    [1.85e-02, 3.96e-01]    []  \n",
      "\n",
      "Best model at step 60000:\n",
      "  train loss: 4.15e-01\n",
      "  test loss: 4.14e-01\n",
      "  test metric: []\n",
      "\n",
      "'train' took 229.976824 s\n",
      "\n",
      "Compiling model...\n",
      "'compile' took 0.000266 s\n",
      "\n",
      "Training model...\n",
      "\n",
      "Step      Train loss              Test loss               Test metric\n",
      "0         [1.67e+07, 4.84e-01]    [1.67e+07, 4.84e-01]    []  \n",
      "1000      [4.19e+03, 3.67e-01]    [4.11e+03, 3.67e-01]    []  \n",
      "2000      [1.74e+03, 3.78e-01]    [1.70e+03, 3.78e-01]    []  \n",
      "3000      [4.55e+02, 3.87e-01]    [4.43e+02, 3.87e-01]    []  \n",
      "4000      [8.22e+01, 3.93e-01]    [7.91e+01, 3.93e-01]    []  \n",
      "5000      [2.46e+01, 3.95e-01]    [2.38e+01, 3.95e-01]    []  \n",
      "6000      [1.25e+01, 3.95e-01]    [1.22e+01, 3.95e-01]    []  \n",
      "7000      [7.65e+00, 3.95e-01]    [7.47e+00, 3.95e-01]    []  \n",
      "8000      [6.33e+00, 3.94e-01]    [6.19e+00, 3.94e-01]    []  \n",
      "9000      [5.78e+00, 3.95e-01]    [5.66e+00, 3.95e-01]    []  \n",
      "10000     [5.21e+00, 3.95e-01]    [5.10e+00, 3.95e-01]    []  \n",
      "11000     [8.36e+00, 3.95e-01]    [8.30e+00, 3.95e-01]    []  \n",
      "12000     [2.62e+01, 3.94e-01]    [2.61e+01, 3.94e-01]    []  \n",
      "13000     [4.09e+00, 3.95e-01]    [3.98e+00, 3.95e-01]    []  \n",
      "14000     [8.71e+00, 3.95e-01]    [8.58e+00, 3.95e-01]    []  \n",
      "15000     [2.80e+00, 3.96e-01]    [2.71e+00, 3.96e-01]    []  \n",
      "16000     [2.09e+00, 3.96e-01]    [2.03e+00, 3.96e-01]    []  \n",
      "17000     [3.74e+00, 3.96e-01]    [3.70e+00, 3.96e-01]    []  \n",
      "18000     [1.54e+00, 3.96e-01]    [1.48e+00, 3.96e-01]    []  \n",
      "19000     [1.31e+00, 3.96e-01]    [1.26e+00, 3.96e-01]    []  \n",
      "20000     [4.79e+00, 3.96e-01]    [4.77e+00, 3.96e-01]    []  \n",
      "21000     [1.02e+00, 3.96e-01]    [9.77e-01, 3.96e-01]    []  \n",
      "22000     [9.10e-01, 3.96e-01]    [8.74e-01, 3.96e-01]    []  \n",
      "23000     [8.24e-01, 3.96e-01]    [7.91e-01, 3.96e-01]    []  \n",
      "24000     [7.62e-01, 3.96e-01]    [7.31e-01, 3.96e-01]    []  \n",
      "25000     [6.90e-01, 3.96e-01]    [6.62e-01, 3.96e-01]    []  \n",
      "26000     [6.41e-01, 3.96e-01]    [6.15e-01, 3.96e-01]    []  \n",
      "27000     [6.28e+00, 3.96e-01]    [6.28e+00, 3.96e-01]    []  \n",
      "28000     [5.62e-01, 3.96e-01]    [5.39e-01, 3.96e-01]    []  \n",
      "29000     [5.32e-01, 3.96e-01]    [5.10e-01, 3.96e-01]    []  \n",
      "30000     [1.19e+00, 3.96e-01]    [1.16e+00, 3.96e-01]    []  \n",
      "31000     [4.85e-01, 3.96e-01]    [4.66e-01, 3.96e-01]    []  \n",
      "32000     [4.64e-01, 3.96e-01]    [4.44e-01, 3.96e-01]    []  \n",
      "33000     [4.49e-01, 3.96e-01]    [4.31e-01, 3.96e-01]    []  \n",
      "34000     [1.77e+01, 3.96e-01]    [1.77e+01, 3.96e-01]    []  \n",
      "35000     [4.15e-01, 3.96e-01]    [3.98e-01, 3.96e-01]    []  \n",
      "36000     [1.81e+01, 3.96e-01]    [1.81e+01, 3.96e-01]    []  \n",
      "37000     [3.89e-01, 3.96e-01]    [3.73e-01, 3.96e-01]    []  \n",
      "38000     [3.79e-01, 3.96e-01]    [3.63e-01, 3.96e-01]    []  \n",
      "39000     [3.69e-01, 3.96e-01]    [3.54e-01, 3.96e-01]    []  \n",
      "40000     [3.54e+00, 3.96e-01]    [3.54e+00, 3.96e-01]    []  \n",
      "41000     [1.34e+01, 3.97e-01]    [1.33e+01, 3.97e-01]    []  \n",
      "42000     [1.27e+01, 3.97e-01]    [1.27e+01, 3.97e-01]    []  \n",
      "43000     [3.69e+00, 3.97e-01]    [3.65e+00, 3.97e-01]    []  \n",
      "44000     [3.27e-01, 3.96e-01]    [3.14e-01, 3.96e-01]    []  \n",
      "45000     [8.93e-01, 3.96e-01]    [8.68e-01, 3.96e-01]    []  \n",
      "46000     [3.14e-01, 3.96e-01]    [3.01e-01, 3.96e-01]    []  \n",
      "47000     [3.92e-01, 3.96e-01]    [3.82e-01, 3.96e-01]    []  \n",
      "48000     [3.01e-01, 3.96e-01]    [2.89e-01, 3.96e-01]    []  \n",
      "49000     [2.96e-01, 3.96e-01]    [2.83e-01, 3.96e-01]    []  \n",
      "50000     [1.84e+01, 3.97e-01]    [1.85e+01, 3.97e-01]    []  \n",
      "51000     [2.92e-01, 3.96e-01]    [2.79e-01, 3.96e-01]    []  \n",
      "52000     [8.06e+01, 3.95e-01]    [8.08e+01, 3.95e-01]    []  \n",
      "53000     [2.74e-01, 3.96e-01]    [2.63e-01, 3.96e-01]    []  \n",
      "54000     [2.69e-01, 3.96e-01]    [2.58e-01, 3.96e-01]    []  \n",
      "55000     [2.64e-01, 3.96e-01]    [2.53e-01, 3.96e-01]    []  \n",
      "56000     [2.60e-01, 3.96e-01]    [2.49e-01, 3.96e-01]    []  \n",
      "57000     [2.60e-01, 3.96e-01]    [2.50e-01, 3.96e-01]    []  \n",
      "58000     [2.51e-01, 3.96e-01]    [2.40e-01, 3.96e-01]    []  \n",
      "59000     [2.46e-01, 3.96e-01]    [2.36e-01, 3.96e-01]    []  \n",
      "60000     [2.43e-01, 3.96e-01]    [2.33e-01, 3.96e-01]    []  \n",
      "\n",
      "Best model at step 60000:\n",
      "  train loss: 6.39e-01\n",
      "  test loss: 6.29e-01\n",
      "  test metric: []\n",
      "\n",
      "'train' took 419.519035 s\n",
      "\n"
     ]
    }
   ],
   "source": [
    "PDECase = Helmholtz(improved=True)\n",
    "cFPCT_DNN_test = cFPCT_DNN(PDECase=PDECase)\n",
    "cFPCT_DNN_test.train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(4.8232, requires_grad=True)\n",
      "tensor(1.6896)\n"
     ]
    }
   ],
   "source": [
    "print(cFPCT_DNN_test.FP.v)\n",
    "print(cFPCT_DNN_test.v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PDECase.plot(cFPCT_DNN_test.FP, title=f\"FP v={cFPCT_DNN_test.FP.v}\")\n",
    "\n",
    "PDECase.plot(cFPCT_DNN_test, title=f\"cFPCT_DNN v={cFPCT_DNN_test.v}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "CaseList = [HighFrequencyCase1(), HighFrequencyCase2(), HighFrequencyCase3(), AKG(), AKG(improved=True), Helmholtz(), Helmholtz(improved=True)]\n",
    "for PDECase in CaseList:\n",
    "    PDECase.plot(title=PDECase.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TDCase_list = [HighFrequencyCase2D1()]\n",
    "for PDECase in TDCase_list:\n",
    "    PDECase.plot(title=PDECase.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linears.0.weight : torch.Size([200, 1])\n",
      "linears.0.bias : torch.Size([200])\n",
      "linears.1.weight : torch.Size([1, 200])\n",
      "linears.1.bias : torch.Size([1])\n",
      "Parameter containing:\n",
      "tensor([[-2.3282e-02],\n",
      "        [ 2.1673e-01],\n",
      "        [-1.1516e-01],\n",
      "        [-2.3841e-02],\n",
      "        [ 1.0281e-01],\n",
      "        [ 1.7132e-01],\n",
      "        [ 1.4120e-01],\n",
      "        [-8.3533e-02],\n",
      "        [-8.3832e-02],\n",
      "        [-2.5872e-01],\n",
      "        [-9.6584e-02],\n",
      "        [-8.6699e-02],\n",
      "        [ 4.7030e-02],\n",
      "        [ 3.4657e-04],\n",
      "        [ 8.9535e-02],\n",
      "        [ 4.9104e-02],\n",
      "        [ 6.7173e-02],\n",
      "        [-1.2789e-01],\n",
      "        [-1.5914e-01],\n",
      "        [ 7.9796e-02],\n",
      "        [ 7.7704e-02],\n",
      "        [-1.0517e-01],\n",
      "        [-2.9160e-01],\n",
      "        [ 1.5573e-01],\n",
      "        [-1.1151e-01],\n",
      "        [ 3.6426e-02],\n",
      "        [ 2.5662e-02],\n",
      "        [ 1.3107e-03],\n",
      "        [-4.1961e-02],\n",
      "        [ 1.4327e-01],\n",
      "        [ 7.4801e-02],\n",
      "        [-1.5952e-01],\n",
      "        [ 1.0012e-01],\n",
      "        [ 1.9177e-02],\n",
      "        [-6.4057e-02],\n",
      "        [-2.2827e-02],\n",
      "        [-3.5594e-02],\n",
      "        [ 1.0934e-02],\n",
      "        [-4.0892e-05],\n",
      "        [-4.4896e-02],\n",
      "        [-4.9488e-02],\n",
      "        [-7.9543e-02],\n",
      "        [ 1.5934e-01],\n",
      "        [ 1.7957e-01],\n",
      "        [-6.3607e-02],\n",
      "        [ 2.2501e-05],\n",
      "        [-1.5072e-02],\n",
      "        [-2.3932e-03],\n",
      "        [ 1.1521e-03],\n",
      "        [-1.9110e-01],\n",
      "        [ 6.7347e-02],\n",
      "        [-1.9794e-05],\n",
      "        [-6.8794e-02],\n",
      "        [-2.9733e-02],\n",
      "        [-9.6281e-03],\n",
      "        [ 6.9336e-02],\n",
      "        [ 1.0511e-01],\n",
      "        [ 8.0289e-02],\n",
      "        [-3.2546e-02],\n",
      "        [-1.4488e-02],\n",
      "        [-3.3334e-02],\n",
      "        [-2.0366e-03],\n",
      "        [ 3.9206e-02],\n",
      "        [-1.9764e-06],\n",
      "        [ 1.5771e-01],\n",
      "        [-8.2057e-03],\n",
      "        [ 2.3075e-02],\n",
      "        [-1.0433e-01],\n",
      "        [-1.2610e-01],\n",
      "        [-8.9068e-03],\n",
      "        [ 5.1326e-05],\n",
      "        [-7.1874e-03],\n",
      "        [ 6.9870e-02],\n",
      "        [ 1.9329e-01],\n",
      "        [-4.5513e-02],\n",
      "        [-6.2245e-02],\n",
      "        [ 8.7285e-02],\n",
      "        [ 2.1254e-01],\n",
      "        [ 1.4840e-01],\n",
      "        [ 5.1734e-02],\n",
      "        [ 2.1708e-05],\n",
      "        [ 1.2932e-01],\n",
      "        [ 4.5467e-02],\n",
      "        [-3.8959e-02],\n",
      "        [ 1.0227e-01],\n",
      "        [-2.4866e-02],\n",
      "        [ 2.1465e-02],\n",
      "        [ 8.8194e-02],\n",
      "        [-7.7292e-02],\n",
      "        [-1.3760e-01],\n",
      "        [-1.1231e-01],\n",
      "        [ 2.0619e-01],\n",
      "        [-1.6467e-01],\n",
      "        [ 4.4399e-02],\n",
      "        [-4.0435e-02],\n",
      "        [-2.9550e-03],\n",
      "        [-1.2844e-01],\n",
      "        [ 2.1222e-02],\n",
      "        [-2.4514e-02],\n",
      "        [ 1.5913e-01],\n",
      "        [ 1.3250e-01],\n",
      "        [-5.5286e-02],\n",
      "        [-2.9205e-02],\n",
      "        [ 9.5111e-03],\n",
      "        [-3.3604e-03],\n",
      "        [ 1.6247e-02],\n",
      "        [ 1.8412e-02],\n",
      "        [ 1.1089e-01],\n",
      "        [ 3.8091e-02],\n",
      "        [ 4.0229e-02],\n",
      "        [ 4.1140e-02],\n",
      "        [ 2.9562e-02],\n",
      "        [-3.2509e-02],\n",
      "        [-1.2803e-01],\n",
      "        [-9.6839e-02],\n",
      "        [ 3.0717e-02],\n",
      "        [-2.1261e-02],\n",
      "        [-5.0540e-02],\n",
      "        [ 1.0810e-01],\n",
      "        [ 8.6524e-02],\n",
      "        [-1.3962e-01],\n",
      "        [-3.8872e-02],\n",
      "        [-9.4627e-03],\n",
      "        [ 1.6508e-02],\n",
      "        [ 3.6562e-02],\n",
      "        [-5.8159e-02],\n",
      "        [-2.1121e-01],\n",
      "        [ 1.4338e-01],\n",
      "        [ 4.4181e-02],\n",
      "        [ 6.3241e-02],\n",
      "        [ 2.1828e-01],\n",
      "        [-1.3155e-01],\n",
      "        [ 1.3628e-01],\n",
      "        [ 6.5823e-02],\n",
      "        [ 6.5209e-02],\n",
      "        [ 9.9538e-02],\n",
      "        [-1.3225e-02],\n",
      "        [ 1.6338e-01],\n",
      "        [ 1.6280e-01],\n",
      "        [ 1.4176e-05],\n",
      "        [-1.4768e-01],\n",
      "        [ 2.5403e-01],\n",
      "        [ 6.2982e-02],\n",
      "        [ 3.8160e-02],\n",
      "        [-1.6383e-01],\n",
      "        [-1.8676e-01],\n",
      "        [ 7.1605e-02],\n",
      "        [ 2.6926e-03],\n",
      "        [-1.2695e-01],\n",
      "        [ 1.7279e-01],\n",
      "        [-1.9977e-02],\n",
      "        [ 5.9533e-02],\n",
      "        [ 9.5588e-02],\n",
      "        [ 6.3303e-02],\n",
      "        [ 2.2380e-02],\n",
      "        [ 4.0974e-02],\n",
      "        [ 9.4873e-02],\n",
      "        [-4.8610e-02],\n",
      "        [-7.0398e-02],\n",
      "        [-6.0451e-02],\n",
      "        [-9.7129e-02],\n",
      "        [ 1.4640e-02],\n",
      "        [ 6.3011e-02],\n",
      "        [-1.3165e-01],\n",
      "        [-1.0276e-02],\n",
      "        [-9.7954e-02],\n",
      "        [ 4.2773e-02],\n",
      "        [ 2.2641e-02],\n",
      "        [-6.6729e-02],\n",
      "        [ 6.2750e-02],\n",
      "        [-1.6466e-01],\n",
      "        [ 6.9590e-02],\n",
      "        [ 6.6992e-02],\n",
      "        [ 9.6586e-02],\n",
      "        [ 4.1003e-02],\n",
      "        [ 2.1634e-01],\n",
      "        [ 1.0214e-01],\n",
      "        [-1.0023e-01],\n",
      "        [ 1.1531e-02],\n",
      "        [-5.2209e-02],\n",
      "        [ 2.1816e-01],\n",
      "        [ 1.4543e-01],\n",
      "        [ 9.5055e-02],\n",
      "        [ 7.2918e-02],\n",
      "        [ 7.5446e-02],\n",
      "        [ 1.2009e-01],\n",
      "        [ 6.9548e-02],\n",
      "        [-5.1277e-02],\n",
      "        [ 6.4382e-03],\n",
      "        [ 3.5709e-02],\n",
      "        [-1.3060e-01],\n",
      "        [ 1.3442e-01],\n",
      "        [ 3.4464e-02],\n",
      "        [ 1.1110e-01],\n",
      "        [-3.1238e-02],\n",
      "        [-4.9222e-02],\n",
      "        [ 4.0686e-03],\n",
      "        [ 3.4974e-02],\n",
      "        [-2.8358e-02],\n",
      "        [ 5.2035e-05]], requires_grad=True)\n",
      "Parameter containing:\n",
      "tensor([ 2.4034e-03, -1.5479e-03,  6.9538e-04,  2.2554e-03, -5.4169e-04,\n",
      "        -2.1379e-03, -3.0359e-04, -5.3921e-05,  2.7813e-05,  4.1592e-03,\n",
      "        -1.2839e-03, -6.1388e-04,  9.5468e-04, -7.0154e-04,  2.8369e-04,\n",
      "        -1.3190e-03, -4.2253e-04,  9.8956e-04, -2.1084e-03,  1.2812e-03,\n",
      "        -2.7061e-04, -2.6277e-03, -1.6761e-03, -8.9201e-04,  9.9599e-04,\n",
      "        -1.3218e-03, -2.0965e-03, -2.7342e-03,  1.6216e-03,  3.8405e-04,\n",
      "        -2.1244e-04, -1.8989e-03,  9.9043e-04, -2.1078e-03, -7.2857e-04,\n",
      "        -1.7128e-03,  1.7946e-03,  1.3735e-04,  3.3199e-05, -1.1647e-03,\n",
      "        -9.2270e-04, -2.4115e-04, -7.7986e-04,  1.1823e-03, -1.1800e-03,\n",
      "         3.4415e-05, -5.3025e-04,  2.9772e-03, -2.5424e-03, -6.5824e-04,\n",
      "        -6.3643e-04,  1.6075e-05, -5.1197e-04, -9.4761e-04,  3.8115e-03,\n",
      "         1.0901e-03,  5.9915e-03,  1.2098e-04, -1.0399e-03, -4.4520e-04,\n",
      "        -1.1170e-03,  4.3899e-03, -1.6007e-03,  4.2870e-05,  2.1916e-03,\n",
      "         2.4592e-04, -2.1908e-03, -1.2255e-03,  2.7369e-04,  4.0245e-03,\n",
      "        -4.4216e-05, -4.8025e-03,  6.6066e-04, -2.2557e-05,  1.2218e-03,\n",
      "        -2.0225e-04,  4.6784e-04, -4.7485e-04, -5.5290e-04, -1.2066e-03,\n",
      "         4.9500e-05, -1.2837e-03,  2.1424e-03,  1.7035e-03, -4.4893e-04,\n",
      "         1.5160e-03,  7.9960e-04,  3.9588e-04, -5.7878e-04, -2.5291e-03,\n",
      "        -1.4702e-03,  8.4111e-04, -1.8995e-03, -1.4675e-03, -1.3015e-03,\n",
      "         6.4035e-03, -1.8655e-03, -2.4445e-03,  1.6861e-03,  2.1459e-02,\n",
      "         1.1235e-02, -3.5693e-03,  2.1167e-03, -3.8669e-03,  7.2543e-03,\n",
      "         6.2931e-04, -2.6211e-03, -9.6039e-04,  2.8501e-02,  9.7109e-04,\n",
      "         9.6937e-04,  9.8700e-04, -1.2620e-03,  1.2755e-03, -1.5914e-03,\n",
      "        -2.0522e-03, -8.3549e-04,  9.6995e-04,  1.0942e-03,  1.9926e-04,\n",
      "        -3.8194e-03, -1.0347e-03,  3.8592e-03,  5.9201e-04, -9.8388e-04,\n",
      "        -8.2807e-04, -9.7183e-04,  2.0627e-03, -9.1474e-04, -7.5017e-04,\n",
      "        -8.5772e-04,  9.4194e-04,  1.9220e-03,  6.4553e-04, -7.8609e-04,\n",
      "         1.7959e-03, -5.1786e-04,  1.8615e-03,  1.8299e-03, -7.3910e-05,\n",
      "         4.8076e-04, -3.0525e-03,  1.0816e-03,  1.1283e-03, -1.2406e-02,\n",
      "         1.1363e-04,  4.2735e-04, -5.7982e-03, -1.8976e-03, -4.8874e-04,\n",
      "         2.2586e-03, -8.9161e-04,  5.6680e-04, -7.8093e-04,  1.1183e-03,\n",
      "         1.2923e-02, -3.9641e-04,  1.4095e-03, -1.7377e-03, -7.7759e-04,\n",
      "        -1.7377e-03,  5.2843e-04, -8.6631e-04, -1.9414e-03, -5.2489e-05,\n",
      "        -8.1208e-04,  1.1417e-03, -2.3856e-03, -1.0992e-03, -8.7799e-04,\n",
      "        -1.9730e-03, -5.0343e-04,  7.1431e-04, -3.2301e-04,  9.7860e-04,\n",
      "         1.3227e-03,  2.4737e-03,  5.8147e-04, -3.4700e-03,  1.2913e-03,\n",
      "         1.2088e-03,  2.4454e-03,  6.2255e-04, -3.6421e-04,  4.7359e-04,\n",
      "         1.5360e-03,  4.9801e-04, -8.5453e-04, -7.9812e-04,  1.1050e-03,\n",
      "         7.3060e-04, -1.2229e-03, -1.6757e-03, -6.6934e-04,  2.0003e-03,\n",
      "         1.2831e-03, -1.7791e-03, -1.0888e-03, -1.1123e-03,  8.2567e-05],\n",
      "       requires_grad=True)\n",
      "Parameter containing:\n",
      "tensor([[ 1.5337e-01,  9.9111e-03, -4.2150e-02,  4.9296e-02, -7.1351e-02,\n",
      "          5.9096e-06, -1.9853e-02, -1.0135e-01, -1.9282e-01,  3.4191e-02,\n",
      "          2.2274e-02,  2.8434e-02, -9.9013e-02, -1.2650e-02, -2.6805e-02,\n",
      "          7.5261e-02,  3.5484e-02, -5.5112e-02,  6.3228e-02,  9.0339e-03,\n",
      "          2.9546e-01,  1.0822e-02, -5.0547e-02, -1.8933e-01, -2.4731e-01,\n",
      "          1.4728e-02,  3.5277e-02, -1.4235e-02,  1.1101e-01, -1.1412e-02,\n",
      "          5.7273e-02,  1.4115e-01,  5.7066e-02,  1.2361e-02, -5.7980e-02,\n",
      "         -1.0092e-02,  6.5187e-02, -6.5880e-02,  1.8884e-02, -3.5604e-02,\n",
      "         -9.9422e-02, -7.3852e-02, -1.8482e-01,  5.4956e-02,  4.4462e-03,\n",
      "          2.7567e-03, -8.3292e-02, -3.7280e-02, -1.2191e-01,  3.3852e-02,\n",
      "          1.0080e-01,  1.0770e-01, -1.0268e-01, -2.1922e-01,  8.3442e-02,\n",
      "         -1.8270e-02, -2.2221e-03, -1.4284e-01, -7.8545e-02, -1.6433e-01,\n",
      "         -4.8427e-02,  8.3254e-02,  4.5900e-02, -1.6289e-03,  5.4428e-02,\n",
      "         -3.2070e-02,  3.0101e-02,  5.0200e-02, -1.8741e-02,  1.2673e-01,\n",
      "         -3.1240e-02, -5.9784e-02, -4.2938e-02, -2.3323e-02,  2.6995e-02,\n",
      "          9.2456e-03,  4.2573e-02,  8.1630e-02, -3.1729e-02,  6.8295e-02,\n",
      "         -1.6984e-01, -2.1094e-01, -8.6998e-03,  8.4881e-02, -5.5037e-02,\n",
      "          5.0939e-03, -1.7223e-01,  6.3101e-02, -3.1002e-02,  3.1492e-02,\n",
      "          6.6616e-02, -1.3685e-01,  5.7632e-02,  6.3578e-02, -2.5793e-02,\n",
      "          1.2828e-01,  1.0017e-01,  6.4985e-02,  1.0330e-02,  4.0419e-07,\n",
      "         -9.6379e-04, -4.3095e-03,  1.3272e-01,  1.1902e-01,  6.9240e-03,\n",
      "         -6.8131e-02,  5.8795e-02, -2.0143e-01, -2.5724e-02, -1.7255e-01,\n",
      "         -1.6177e-01, -1.0745e-01, -2.7568e-02, -2.0887e-01,  1.6070e-02,\n",
      "          1.2849e-01, -8.9174e-02,  2.3397e-02,  2.4456e-01,  1.2383e-01,\n",
      "          1.2212e-02, -8.5044e-02,  9.1560e-02, -1.3564e-01,  8.2734e-03,\n",
      "         -6.7557e-02, -5.9047e-02,  9.9290e-02,  1.2662e-02,  6.7623e-02,\n",
      "          7.8309e-02, -4.7570e-02,  1.5354e-01, -7.1090e-02,  2.0241e-01,\n",
      "          1.5325e-02, -3.1550e-02,  9.8940e-02,  1.3815e-01, -5.0357e-02,\n",
      "         -2.7773e-02,  1.2537e-01, -2.2923e-02, -4.7228e-02,  2.3303e-06,\n",
      "         -3.9495e-02, -1.0679e-01,  7.9185e-02,  7.6918e-02, -1.0256e-01,\n",
      "          2.0319e-02,  6.3874e-02,  2.0703e-01,  8.3722e-02, -2.4943e-02,\n",
      "          9.2253e-04, -1.4608e-01,  1.5959e-01, -9.5438e-03, -6.8656e-02,\n",
      "          1.4322e-02, -6.1320e-02,  1.7513e-01,  9.5422e-02, -5.9830e-02,\n",
      "          7.6979e-02, -4.0964e-02,  7.9425e-02, -1.9578e-02,  1.7820e-01,\n",
      "          4.4695e-02,  7.7566e-02, -4.5971e-02, -6.8432e-02, -1.4201e-01,\n",
      "         -1.4722e-01, -5.0846e-03, -1.4125e-01,  1.3969e-01,  2.0131e-01,\n",
      "         -4.1733e-02,  3.8777e-02,  1.0314e-01,  8.1091e-02, -4.7678e-02,\n",
      "          2.0515e-01, -9.7333e-02, -1.6180e-01, -5.8034e-02, -5.3532e-02,\n",
      "         -3.2018e-02, -1.3012e-01,  2.9719e-02, -4.9681e-02,  8.8977e-02,\n",
      "          6.1082e-02, -3.5709e-02,  8.7284e-03, -4.0057e-02,  8.9240e-02]],\n",
      "       requires_grad=True)\n",
      "Parameter containing:\n",
      "tensor([0.0038], requires_grad=True)\n",
      "v=1.0 L2 relative error:0.9999676942825317\n",
      "v=1.2 L2 relative error:0.9999221563339233\n",
      "v=1.4 L2 relative error:0.9999324679374695\n",
      "v=1.5999999999999999 L2 relative error:1.000011682510376\n",
      "v=1.7999999999999998 L2 relative error:1.0000815391540527\n",
      "v=1.9999999999999998 L2 relative error:1.0000168085098267\n",
      "v=2.1999999999999997 L2 relative error:1.00003182888031\n",
      "v=2.3999999999999995 L2 relative error:0.9999695420265198\n",
      "v=2.5999999999999996 L2 relative error:0.9999630451202393\n",
      "v=2.8 L2 relative error:1.0000182390213013\n",
      "v=2.9999999999999996 L2 relative error:0.9999271035194397\n",
      "v=3.1999999999999993 L2 relative error:0.9999618530273438\n",
      "v=3.3999999999999995 L2 relative error:1.0000128746032715\n",
      "v=3.5999999999999996 L2 relative error:0.9999355673789978\n",
      "v=3.7999999999999994 L2 relative error:0.9999712705612183\n",
      "v=3.999999999999999 L2 relative error:0.9999585151672363\n",
      "v=4.199999999999999 L2 relative error:0.9999951720237732\n",
      "v=4.3999999999999995 L2 relative error:0.9999982118606567\n",
      "v=4.6 L2 relative error:1.000002145767212\n",
      "v=4.799999999999999 L2 relative error:1.0000004768371582\n",
      "v=4.999999999999999 L2 relative error:1.000012755393982\n",
      "v=5.199999999999999 L2 relative error:0.9999968409538269\n",
      "v=5.399999999999999 L2 relative error:1.0000112056732178\n",
      "v=5.599999999999999 L2 relative error:1.0000115633010864\n",
      "v=5.799999999999999 L2 relative error:1.000002384185791\n",
      "v=5.999999999999999 L2 relative error:1.0000207424163818\n",
      "v=6.199999999999999 L2 relative error:1.0001354217529297\n",
      "v=6.399999999999999 L2 relative error:1.0001140832901\n",
      "v=6.599999999999999 L2 relative error:1.0000945329666138\n",
      "v=6.799999999999999 L2 relative error:1.000290036201477\n",
      "v=6.999999999999998 L2 relative error:1.0003865957260132\n",
      "v=7.199999999999998 L2 relative error:1.0001945495605469\n",
      "v=7.399999999999999 L2 relative error:1.0004198551177979\n",
      "v=7.599999999999999 L2 relative error:1.0001450777053833\n",
      "v=7.799999999999999 L2 relative error:1.0002377033233643\n",
      "v=7.999999999999998 L2 relative error:1.0003843307495117\n",
      "v=8.2 L2 relative error:1.0010287761688232\n",
      "v=8.399999999999999 L2 relative error:1.0011672973632812\n",
      "v=8.599999999999998 L2 relative error:1.0022612810134888\n",
      "v=8.799999999999997 L2 relative error:1.002503514289856\n",
      "v=8.999999999999998 L2 relative error:1.0005955696105957\n",
      "v=9.199999999999998 L2 relative error:1.0040949583053589\n",
      "v=9.399999999999999 L2 relative error:1.0011461973190308\n",
      "v=9.599999999999998 L2 relative error:1.0017426013946533\n",
      "v=9.799999999999997 L2 relative error:1.0049687623977661\n",
      "v=9.999999999999998 L2 relative error:1.005797028541565\n",
      "v=10.199999999999998 L2 relative error:1.010806918144226\n",
      "v=10.399999999999999 L2 relative error:1.0097101926803589\n",
      "v=10.599999999999998 L2 relative error:1.0023143291473389\n",
      "v=10.799999999999997 L2 relative error:1.0111231803894043\n",
      "v=10.999999999999998 L2 relative error:1.0138204097747803\n",
      "v=11.199999999999998 L2 relative error:1.0059492588043213\n",
      "v=11.399999999999999 L2 relative error:1.0102779865264893\n",
      "v=11.599999999999998 L2 relative error:1.0186383724212646\n",
      "v=11.799999999999997 L2 relative error:1.0121678113937378\n",
      "v=11.999999999999998 L2 relative error:1.0173723697662354\n",
      "v=12.199999999999998 L2 relative error:1.015325665473938\n",
      "v=12.399999999999997 L2 relative error:1.013629674911499\n",
      "v=12.599999999999998 L2 relative error:1.0203533172607422\n",
      "v=12.799999999999997 L2 relative error:1.019090175628662\n",
      "v=12.999999999999996 L2 relative error:1.0201196670532227\n",
      "v=13.199999999999998 L2 relative error:1.0177946090698242\n",
      "v=13.399999999999997 L2 relative error:1.0248501300811768\n",
      "v=13.599999999999998 L2 relative error:1.020276427268982\n",
      "v=13.799999999999997 L2 relative error:1.020186185836792\n",
      "v=13.999999999999996 L2 relative error:1.019246220588684\n",
      "v=14.199999999999998 L2 relative error:1.012972354888916\n",
      "v=14.399999999999997 L2 relative error:1.023088812828064\n",
      "v=14.599999999999998 L2 relative error:1.0204863548278809\n",
      "v=14.799999999999997 L2 relative error:1.0137858390808105\n",
      "v=14.999999999999996 L2 relative error:1.0170069932937622\n",
      "v=15.199999999999998 L2 relative error:1.0242124795913696\n",
      "v=15.399999999999997 L2 relative error:1.0263280868530273\n",
      "v=15.599999999999996 L2 relative error:1.0232151746749878\n",
      "v=15.799999999999997 L2 relative error:1.0197970867156982\n",
      "v=15.999999999999996 L2 relative error:1.0298857688903809\n",
      "v=16.199999999999996 L2 relative error:1.0263861417770386\n",
      "v=16.4 L2 relative error:1.0369542837142944\n",
      "v=16.599999999999994 L2 relative error:1.0348622798919678\n",
      "v=16.799999999999997 L2 relative error:1.048041582107544\n",
      "v=16.999999999999996 L2 relative error:1.0469157695770264\n",
      "v=17.199999999999996 L2 relative error:1.0555143356323242\n",
      "v=17.399999999999995 L2 relative error:1.0520539283752441\n",
      "v=17.599999999999998 L2 relative error:1.0627260208129883\n",
      "v=17.799999999999997 L2 relative error:1.0735958814620972\n",
      "v=17.999999999999996 L2 relative error:1.0631803274154663\n",
      "v=18.199999999999996 L2 relative error:1.0855793952941895\n",
      "v=18.399999999999995 L2 relative error:1.083011507987976\n",
      "v=18.599999999999994 L2 relative error:1.1081680059432983\n",
      "v=18.799999999999997 L2 relative error:1.1262973546981812\n",
      "v=18.999999999999996 L2 relative error:1.1143028736114502\n",
      "v=19.199999999999996 L2 relative error:1.096337080001831\n",
      "v=19.399999999999995 L2 relative error:1.1337169408798218\n",
      "v=19.599999999999994 L2 relative error:1.1265391111373901\n",
      "v=19.799999999999997 L2 relative error:1.118085503578186\n",
      "v=19.999999999999996 L2 relative error:1.1385211944580078\n",
      "v=20.199999999999996 L2 relative error:1.1400779485702515\n",
      "v=20.399999999999995 L2 relative error:1.1266860961914062\n",
      "v=20.599999999999994 L2 relative error:1.1395907402038574\n",
      "v=20.799999999999997 L2 relative error:1.1328716278076172\n",
      "v=20.999999999999996 L2 relative error:1.1288859844207764\n",
      "v=21.199999999999996 L2 relative error:1.103487491607666\n",
      "v=21.399999999999995 L2 relative error:1.1290130615234375\n",
      "v=21.599999999999994 L2 relative error:1.1099772453308105\n",
      "v=21.799999999999997 L2 relative error:1.1383339166641235\n",
      "v=21.999999999999996 L2 relative error:1.1175123453140259\n",
      "v=22.199999999999996 L2 relative error:1.1166232824325562\n",
      "v=22.399999999999995 L2 relative error:1.131827473640442\n",
      "v=22.599999999999994 L2 relative error:1.1288403272628784\n",
      "v=22.799999999999994 L2 relative error:1.1371805667877197\n",
      "v=22.999999999999996 L2 relative error:1.1230393648147583\n",
      "v=23.199999999999996 L2 relative error:1.1408535242080688\n",
      "v=23.399999999999995 L2 relative error:1.1412571668624878\n",
      "v=23.599999999999994 L2 relative error:1.1482394933700562\n",
      "v=23.799999999999994 L2 relative error:1.1623611450195312\n",
      "v=23.999999999999996 L2 relative error:1.1572428941726685\n",
      "v=24.199999999999996 L2 relative error:1.1714584827423096\n",
      "v=24.399999999999995 L2 relative error:1.1948907375335693\n",
      "v=24.599999999999994 L2 relative error:1.199476718902588\n",
      "v=24.799999999999994 L2 relative error:1.210908055305481\n",
      "v=24.999999999999993 L2 relative error:1.219241976737976\n",
      "v=25.199999999999996 L2 relative error:1.201604962348938\n",
      "v=25.399999999999995 L2 relative error:1.2290730476379395\n",
      "v=25.599999999999994 L2 relative error:1.215451955795288\n",
      "v=25.799999999999994 L2 relative error:1.248215913772583\n",
      "v=25.999999999999993 L2 relative error:1.2349070310592651\n",
      "v=26.199999999999996 L2 relative error:1.2852951288223267\n",
      "v=26.399999999999995 L2 relative error:1.258130431175232\n",
      "v=26.599999999999994 L2 relative error:1.244484543800354\n",
      "v=26.799999999999994 L2 relative error:1.2549086809158325\n",
      "v=26.999999999999993 L2 relative error:1.2725995779037476\n",
      "v=27.199999999999996 L2 relative error:1.2389470338821411\n",
      "v=27.399999999999995 L2 relative error:1.2369023561477661\n",
      "v=27.599999999999994 L2 relative error:1.2764769792556763\n",
      "v=27.799999999999994 L2 relative error:1.2594040632247925\n",
      "v=27.999999999999993 L2 relative error:1.2610243558883667\n",
      "v=28.199999999999996 L2 relative error:1.243855357170105\n",
      "v=28.399999999999995 L2 relative error:1.2563142776489258\n",
      "v=28.599999999999994 L2 relative error:1.254126787185669\n",
      "v=28.799999999999994 L2 relative error:1.247039794921875\n",
      "v=28.999999999999993 L2 relative error:1.2657333612442017\n",
      "v=29.199999999999992 L2 relative error:1.2748464345932007\n",
      "v=29.399999999999995 L2 relative error:1.2594430446624756\n",
      "v=29.599999999999994 L2 relative error:1.250314474105835\n",
      "v=29.799999999999994 L2 relative error:1.248353123664856\n",
      "v=29.999999999999993 L2 relative error:1.2585381269454956\n",
      "v=30.199999999999992 L2 relative error:1.24591064453125\n",
      "v=30.399999999999995 L2 relative error:1.2459810972213745\n",
      "v=30.599999999999994 L2 relative error:1.2536580562591553\n",
      "v=30.799999999999994 L2 relative error:1.2260173559188843\n",
      "v=30.999999999999993 L2 relative error:1.2411619424819946\n",
      "v=31.199999999999992 L2 relative error:1.2565995454788208\n",
      "v=31.39999999999999 L2 relative error:1.2463656663894653\n",
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      "v=32.19999999999999 L2 relative error:1.2512973546981812\n",
      "v=32.39999999999999 L2 relative error:1.2551887035369873\n",
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      "v=32.8 L2 relative error:1.2768795490264893\n",
      "v=32.99999999999999 L2 relative error:1.2648873329162598\n",
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      "v=34.199999999999996 L2 relative error:1.2802996635437012\n",
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      "v=35.199999999999996 L2 relative error:1.3221460580825806\n",
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      "v=36.19999999999999 L2 relative error:1.2786842584609985\n",
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      "v=66.19999999999999 L2 relative error:1.3520842790603638\n",
      "v=66.39999999999999 L2 relative error:1.3786170482635498\n",
      "v=66.59999999999998 L2 relative error:1.3386833667755127\n",
      "v=66.79999999999998 L2 relative error:1.3602415323257446\n",
      "v=66.99999999999999 L2 relative error:1.376166582107544\n",
      "v=67.19999999999999 L2 relative error:1.3630669116973877\n",
      "v=67.39999999999999 L2 relative error:1.3396596908569336\n",
      "v=67.59999999999998 L2 relative error:1.3708326816558838\n",
      "v=67.79999999999998 L2 relative error:1.3735860586166382\n",
      "v=67.99999999999999 L2 relative error:1.3647791147232056\n",
      "v=68.19999999999999 L2 relative error:1.3480591773986816\n",
      "v=68.39999999999999 L2 relative error:1.348995327949524\n",
      "v=68.59999999999998 L2 relative error:1.3500943183898926\n",
      "v=68.79999999999998 L2 relative error:1.3795809745788574\n",
      "v=68.99999999999999 L2 relative error:1.3447859287261963\n",
      "v=69.19999999999999 L2 relative error:1.4025191068649292\n",
      "v=69.39999999999999 L2 relative error:1.3379191160202026\n",
      "v=69.59999999999998 L2 relative error:1.3373591899871826\n",
      "v=69.79999999999998 L2 relative error:1.3991016149520874\n",
      "v=69.99999999999999 L2 relative error:1.4080140590667725\n",
      "v=70.19999999999999 L2 relative error:1.3946648836135864\n",
      "v=70.39999999999999 L2 relative error:1.374526858329773\n",
      "v=70.59999999999998 L2 relative error:1.3979915380477905\n",
      "v=70.79999999999998 L2 relative error:1.3707289695739746\n",
      "v=70.99999999999999 L2 relative error:1.40030837059021\n",
      "v=71.19999999999999 L2 relative error:1.4059923887252808\n",
      "v=71.39999999999998 L2 relative error:1.3652974367141724\n",
      "v=71.59999999999998 L2 relative error:1.4239213466644287\n",
      "v=71.79999999999998 L2 relative error:1.3973338603973389\n",
      "v=71.99999999999999 L2 relative error:1.4010069370269775\n",
      "v=72.19999999999999 L2 relative error:1.4059187173843384\n",
      "v=72.39999999999998 L2 relative error:1.4069206714630127\n",
      "v=72.59999999999998 L2 relative error:1.435716986656189\n",
      "v=72.79999999999998 L2 relative error:1.431343913078308\n",
      "v=72.99999999999999 L2 relative error:1.427822232246399\n",
      "v=73.19999999999999 L2 relative error:1.446055293083191\n",
      "v=73.39999999999998 L2 relative error:1.4250706434249878\n",
      "v=73.59999999999998 L2 relative error:1.4590907096862793\n",
      "v=73.79999999999998 L2 relative error:1.4321954250335693\n",
      "v=73.99999999999999 L2 relative error:1.4321259260177612\n",
      "v=74.19999999999999 L2 relative error:1.4455231428146362\n",
      "v=74.39999999999998 L2 relative error:1.437198281288147\n",
      "v=74.59999999999998 L2 relative error:1.467309594154358\n",
      "v=74.79999999999998 L2 relative error:1.40506112575531\n",
      "v=74.99999999999999 L2 relative error:1.4308348894119263\n",
      "v=75.19999999999999 L2 relative error:1.4248573780059814\n",
      "v=75.39999999999998 L2 relative error:1.4461331367492676\n",
      "v=75.59999999999998 L2 relative error:1.4288185834884644\n",
      "v=75.79999999999998 L2 relative error:1.405779480934143\n",
      "v=75.99999999999999 L2 relative error:1.43953537940979\n",
      "v=76.19999999999999 L2 relative error:1.4378607273101807\n",
      "v=76.39999999999998 L2 relative error:1.4267157316207886\n",
      "v=76.59999999999998 L2 relative error:1.416963815689087\n",
      "v=76.79999999999998 L2 relative error:1.4303340911865234\n",
      "v=76.99999999999999 L2 relative error:1.4172179698944092\n",
      "v=77.19999999999999 L2 relative error:1.4103007316589355\n",
      "v=77.39999999999998 L2 relative error:1.4331135749816895\n",
      "v=77.59999999999998 L2 relative error:1.4229450225830078\n",
      "v=77.79999999999998 L2 relative error:1.3925495147705078\n",
      "v=77.99999999999999 L2 relative error:1.414921760559082\n",
      "v=78.19999999999999 L2 relative error:1.4425256252288818\n",
      "v=78.39999999999998 L2 relative error:1.4346963167190552\n",
      "v=78.59999999999998 L2 relative error:1.4207578897476196\n",
      "v=78.79999999999998 L2 relative error:1.4313334226608276\n",
      "v=78.99999999999999 L2 relative error:1.4189417362213135\n",
      "v=79.19999999999999 L2 relative error:1.3995050191879272\n",
      "v=79.39999999999998 L2 relative error:1.435299038887024\n",
      "v=79.59999999999998 L2 relative error:1.4161500930786133\n",
      "v=79.79999999999998 L2 relative error:1.3768318891525269\n",
      "v=79.99999999999999 L2 relative error:1.4442362785339355\n",
      "v=80.19999999999999 L2 relative error:1.4039429426193237\n",
      "v=80.39999999999998 L2 relative error:1.3901360034942627\n",
      "v=80.59999999999998 L2 relative error:1.3998451232910156\n",
      "v=80.79999999999998 L2 relative error:1.4157737493515015\n",
      "v=80.99999999999999 L2 relative error:1.4111894369125366\n",
      "v=81.19999999999999 L2 relative error:1.3996235132217407\n",
      "v=81.39999999999998 L2 relative error:1.3928827047348022\n",
      "v=81.59999999999998 L2 relative error:1.423779845237732\n",
      "v=81.79999999999998 L2 relative error:1.412890076637268\n",
      "v=81.99999999999999 L2 relative error:1.3805186748504639\n",
      "v=82.19999999999999 L2 relative error:1.4003138542175293\n",
      "v=82.39999999999998 L2 relative error:1.403063416481018\n",
      "v=82.59999999999998 L2 relative error:1.3678946495056152\n",
      "v=82.79999999999998 L2 relative error:1.4266517162322998\n",
      "v=82.99999999999999 L2 relative error:1.3993569612503052\n",
      "v=83.19999999999999 L2 relative error:1.4076048135757446\n",
      "v=83.39999999999998 L2 relative error:1.400739073753357\n",
      "v=83.59999999999998 L2 relative error:1.4265002012252808\n",
      "v=83.79999999999998 L2 relative error:1.4174129962921143\n",
      "v=83.99999999999999 L2 relative error:1.4274553060531616\n",
      "v=84.19999999999999 L2 relative error:1.4222285747528076\n",
      "v=84.39999999999998 L2 relative error:1.466531753540039\n",
      "v=84.59999999999998 L2 relative error:1.4325734376907349\n",
      "v=84.79999999999998 L2 relative error:1.4071274995803833\n",
      "v=84.99999999999999 L2 relative error:1.4285802841186523\n",
      "v=85.19999999999997 L2 relative error:1.4366496801376343\n",
      "v=85.39999999999998 L2 relative error:1.4554522037506104\n",
      "v=85.59999999999998 L2 relative error:1.438419222831726\n",
      "v=85.79999999999998 L2 relative error:1.4660546779632568\n",
      "v=85.99999999999999 L2 relative error:1.5065680742263794\n",
      "v=86.19999999999997 L2 relative error:1.4631617069244385\n",
      "v=86.39999999999998 L2 relative error:1.4478682279586792\n",
      "v=86.59999999999998 L2 relative error:1.4853169918060303\n",
      "v=86.79999999999998 L2 relative error:1.5251185894012451\n",
      "v=86.99999999999999 L2 relative error:1.4696844816207886\n",
      "v=87.19999999999997 L2 relative error:1.46548593044281\n",
      "v=87.39999999999998 L2 relative error:1.4707714319229126\n",
      "v=87.59999999999998 L2 relative error:1.4919803142547607\n",
      "v=87.79999999999998 L2 relative error:1.5069141387939453\n",
      "v=87.99999999999999 L2 relative error:1.5189448595046997\n",
      "v=88.19999999999997 L2 relative error:1.4876478910446167\n",
      "v=88.39999999999998 L2 relative error:1.5031465291976929\n",
      "v=88.59999999999998 L2 relative error:1.493627667427063\n",
      "v=88.79999999999998 L2 relative error:1.4643079042434692\n",
      "v=88.99999999999999 L2 relative error:1.4915392398834229\n",
      "v=89.19999999999997 L2 relative error:1.4808632135391235\n",
      "v=89.39999999999998 L2 relative error:1.5059763193130493\n",
      "v=89.59999999999998 L2 relative error:1.475700855255127\n",
      "v=89.79999999999998 L2 relative error:1.4897557497024536\n",
      "v=89.99999999999999 L2 relative error:1.519507646560669\n",
      "v=90.19999999999997 L2 relative error:1.5161856412887573\n",
      "v=90.39999999999998 L2 relative error:1.4889930486679077\n",
      "v=90.59999999999998 L2 relative error:1.529720664024353\n",
      "v=90.79999999999998 L2 relative error:1.488384485244751\n",
      "v=90.99999999999999 L2 relative error:1.5518798828125\n",
      "v=91.19999999999997 L2 relative error:1.5233280658721924\n",
      "v=91.39999999999998 L2 relative error:1.490340232849121\n",
      "v=91.59999999999998 L2 relative error:1.5334826707839966\n",
      "v=91.79999999999998 L2 relative error:1.537781834602356\n",
      "v=91.99999999999999 L2 relative error:1.530685544013977\n",
      "v=92.19999999999997 L2 relative error:1.538122296333313\n",
      "v=92.39999999999998 L2 relative error:1.5027793645858765\n",
      "v=92.59999999999998 L2 relative error:1.5474910736083984\n",
      "v=92.79999999999998 L2 relative error:1.5431251525878906\n",
      "v=92.99999999999999 L2 relative error:1.5324232578277588\n",
      "v=93.19999999999997 L2 relative error:1.46781325340271\n",
      "v=93.39999999999998 L2 relative error:1.5406498908996582\n",
      "v=93.59999999999998 L2 relative error:1.5303230285644531\n",
      "v=93.79999999999998 L2 relative error:1.5139533281326294\n",
      "v=93.99999999999999 L2 relative error:1.5177216529846191\n",
      "v=94.19999999999997 L2 relative error:1.5177725553512573\n",
      "v=94.39999999999998 L2 relative error:1.5729392766952515\n",
      "v=94.59999999999998 L2 relative error:1.5071979761123657\n",
      "v=94.79999999999998 L2 relative error:1.505792260169983\n",
      "v=94.99999999999999 L2 relative error:1.5176585912704468\n",
      "v=95.19999999999997 L2 relative error:1.5159004926681519\n",
      "v=95.39999999999998 L2 relative error:1.4874953031539917\n",
      "v=95.59999999999998 L2 relative error:1.5266263484954834\n",
      "v=95.79999999999998 L2 relative error:1.5433694124221802\n",
      "v=95.99999999999999 L2 relative error:1.492269515991211\n",
      "v=96.19999999999997 L2 relative error:1.4940145015716553\n",
      "v=96.39999999999998 L2 relative error:1.5696693658828735\n",
      "v=96.59999999999998 L2 relative error:1.529133915901184\n",
      "v=96.79999999999998 L2 relative error:1.531614065170288\n",
      "v=96.99999999999997 L2 relative error:1.4785351753234863\n",
      "v=97.19999999999997 L2 relative error:1.4900128841400146\n",
      "v=97.39999999999998 L2 relative error:1.5129371881484985\n",
      "v=97.59999999999998 L2 relative error:1.5074422359466553\n",
      "v=97.79999999999998 L2 relative error:1.543154001235962\n",
      "v=97.99999999999997 L2 relative error:1.532812237739563\n",
      "v=98.19999999999997 L2 relative error:1.5207545757293701\n",
      "v=98.39999999999998 L2 relative error:1.4986565113067627\n",
      "v=98.59999999999998 L2 relative error:1.4845486879348755\n",
      "v=98.79999999999998 L2 relative error:1.5076490640640259\n",
      "v=98.99999999999997 L2 relative error:1.4725629091262817\n",
      "v=99.19999999999997 L2 relative error:1.4959772825241089\n",
      "v=99.39999999999998 L2 relative error:1.5072669982910156\n",
      "v=99.59999999999998 L2 relative error:1.5065453052520752\n",
      "v=99.79999999999998 L2 relative error:1.5204495191574097\n",
      "min_v=1.2 min_error=0.9999221563339233\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import deepxde as dde\n",
    "\n",
    "for name,parameters in cFPCT_DNN_test.FP.model.net.named_parameters():\n",
    "    print(name,':',parameters.size())\n",
    "\n",
    "for parameters in cFPCT_DNN_test.FP.model.net.parameters():\n",
    "    print(parameters)\n",
    "\n",
    "def eval(model, PDECase):\n",
    "    X, y = PDECase.gen_testdata()\n",
    "    y_pred = model.model.predict(X)\n",
    "    error = dde.metrics.l2_relative_error(y, y_pred)\n",
    "    print(f\"v={model.v} L2 relative error:{error}\")\n",
    "    return error\n",
    "\n",
    "#eval(cFPCT_DNN_test.FP, cFPCT_DNN_test.PDECase)\n",
    "min_error = 100\n",
    "min_v = 0\n",
    "for v in np.arange(1.0,100.0,0.2):\n",
    "    cFPCT_DNN_test.FP.v = torch.tensor(v)\n",
    "    error = eval(cFPCT_DNN_test.FP, cFPCT_DNN_test.PDECase)\n",
    "    if error < min_error:\n",
    "        min_error = error\n",
    "        min_v = v\n",
    "print(f\"min_v={min_v} min_error={min_error}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min_v=2.6000000000000014 min_error=0.9998788833618164\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import deepxde as dde\n",
    "import matplotlib.pyplot as plt\n",
    "from cFPCT_DNN import cFPCT_DNN\n",
    "from TestCases import HighFrequencyCase1, HighFrequencyCase2, HighFrequencyCase3, AKG, Helmholtz, HighFrequencyCase2D1\n",
    "\n",
    "PDECase = Helmholtz()\n",
    "cFPCT_DNN_test = cFPCT_DNN(PDECase=PDECase)\n",
    "cFPCT_DNN_test.FP.train()\n",
    "\n",
    "print(cFPCT_DNN_test.FP.v)\n",
    "\n",
    "def plot_error_at_v(model, start=1.0, end=100.0, step=0.1):\n",
    "    error = []\n",
    "    min_error = 1000\n",
    "    min_v = 0\n",
    "    for i, v in enumerate(np.arange(start, end, step)):\n",
    "        model.FP.v = torch.tensor(v)\n",
    "        error.append(model.FP.eval())\n",
    "        if error[-1] < min_error:\n",
    "            min_error = error[-1]\n",
    "            min_v = v\n",
    "    plt.plot(np.arange(start, end, step), error)\n",
    "    print(f\"min_v={min_v} min_error={min_error}\")\n",
    "    plt.show()\n",
    "\n",
    "plot_error_at_v(cFPCT_DNN_test, start=1.0, end=1000.0, step=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import deepxde as dde\n",
    "import matplotlib.pyplot as plt\n",
    "from cFPCT_DNN import cFPCT_DNN\n",
    "from TestCases import HighFrequencyCase1, HighFrequencyCase2, HighFrequencyCase3, AKG, Helmholtz, HighFrequencyCase2D1\n",
    "\n",
    "PDECase = AKG()\n",
    "cFPCT_DNN_test = cFPCT_DNN(PDECase=PDECase)\n",
    "cFPCT_DNN_test.v = torch.pow(torch.abs(torch.tensor(43.355)), 1/3).detach()\n",
    "print(cFPCT_DNN_test.v)\n",
    "\n",
    "cFPCT_DNN_test.model = dde.Model(cFPCT_DNN_test.PDECase.data, cFPCT_DNN_test.build_net())\n",
    "cFPCT_DNN_test.model.compile(\"adam\", lr=0.01)\n",
    "losshistory, train_state = cFPCT_DNN_test.model.train(iterations=cFPCT_DNN_test.PDECase.max_iter)\n",
    "cFPCT_DNN_test.PDECase.plot(title=f\"cFPCT_DNN v={cFPCT_DNN_test.v}\", model=cFPCT_DNN_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cFPCT_DNN_test.FP.model.compile(\"adam\", lr=0.1, external_trainable_variables=[cFPCT_DNN_test.FP.v], loss_weights=[0.1, 0.01])\n",
    "variable = dde.callbacks.VariableValue([cFPCT_DNN_test.FP.v], period=600, filename=\"variables.dat\")\n",
    "losshistory, train_state = cFPCT_DNN_test.FP.model.train(iterations=40000, callbacks=[variable])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m在当前单元格或上一个单元格中执行代码时 Kernel 崩溃。请查看单元格中的代码，以确定故障的可能原因。有关详细信息，请单击 <a href='https://aka.ms/vscodeJupyterKernelCrash'>此处</a>。有关更多详细信息，请查看 Jupyter <a href='command:jupyter.viewOutput'>log</a>。"
     ]
    }
   ],
   "source": [
    "#cFPCT_DNN_test.v = torch.pow(torch.abs(torch.tensor(100)), 1/3).detach()\n",
    "print(cFPCT_DNN_test.v)\n",
    "X = PDECase.data.train_x\n",
    "plt.plot(X[:, 0], X[:, 1], label='cFPCT_DNN', marker='o', markersize=0.2 , linestyle='None')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pytorch2-0",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
